Unexpected events, such as accidents or track damages, can have a significant impact on the railway system so that trains need to be canceled and delayed. In case of a disruption it is important that dispatchers quickly present a good solution in order to minimize the nuisance for the passengers. In this paper, we focus on adjusting the timetable of a passenger railway operator in case of major disruptions. Both a partial and a complete blockade of a railway line are considered. Given a disrupted infrastructure situation and a forecast of the characteristics of the disruption, our goal is to determine a disposition timetable, specifying which trains will still be operated during the disruption and determining the timetable of these trains. Without explicitly taking the rolling stock rescheduling problem into account, we develop our models such that the probability that feasible solutions to this problem exists, is high. The main objective is to maximize the service level offered to the passengers. We present integer programming formulations and test our models using instances from Netherlands Railways.

AimThis study summarised available evidence on the association between early and on-time retirement, compared with continued working, and mortality. Moreover, this study investigated whether and to what extent gender, adjustment for demographics and prior health status influence this association.MethodsA systematic literature search of longitudinal studies was conducted. A qualitative analysis of the included studies was performed, followed by a meta-regression analysis to assess the influence of gender, prior health and demographics. Random-effects models were used in a meta-analysis to estimate the pooled effects for relevant subgroups identified in the meta-regression.ResultsIn total, 25 studies were included. Adjustment for prior health and demographics influenced the association between retirement and mortality (p<0.05). The results of the meta-analysis of 12 studies are presented for ‘insufficiently adjusted’ and ‘fully adjusted’ subgroups. There was no association between early retirement and mortality compared with working until retirement (fully adjusted subgroup: HR 1.05, 95% CI 0.87 to 1.28). On-time retirement was associated with a higher risk of mortality compared with working beyond retirement (insufficiently adjusted subgroup: HR 1.56, 95% CI 1.41 to 1.73). However, in the subgroup that adjusted for prior health, on-time retirement was not associated with mortality (HR 1.12, 95% CI 0.98 to 1.28).ConclusionEarly retirement was not associated with a higher risk of mortality. On-time retirement was associated with a higher risk of mortality, which might reflect the healthy worker effect. It is important to consider information on prior health and demographics when studying the association between retirement and mortality to avoid biased findings.

BackgroundToday, work disability is one of the greatest social and labour market challenges for policy makers in most OECD countries, where on average, about 6% of the working-age population relies on disability benefits. Understanding of factors associated with long-term work disability may be helpful to identify groups of individuals at risk for disability benefit entitlement or continuing eligibility, and to develop effective interventions for these groups. The purpose of this study is to provide insight into the main diagnoses of workers who qualify for disability benefits and how these diagnoses differ in age, gender and education. Using a five-year follow-up, we examined the duration of disability benefits and how durations differ among individuals with various characteristics.MethodsWe performed a cohort study of 31,733 individuals receiving disability benefits from the Dutch Social Security Institute (SSI) with a five-year follow-up. Data were collected from SSI databases. Information about disorders was assessed by an insurance physician upon benefit application. These data were used to test for significant relationships among socio-demographics, main diagnoses and comorbidity, and disability benefit entitlement and continuing eligibility.ResultsMental disorders were the most frequent diagnosis for individuals claiming work disability. Diagnoses differed among age groups and education categories. Mental disorders were the main diagnosis for work disability for younger and more highly educated individuals, and physical disorders (generally musculoskeletal, cardiovascular and cancer) were the main diagnosis for older and less educated individuals. In 82% of the claims, the duration of disability benefit was five years or more after approval. Outflow was lowest for individuals with (multiple) mental disorders and those with comorbidity of mental and physical disorders, and highest for individuals with (multiple) physical disorders.ConclusionsThe main diagnosis for persons entitled to disability benefits was mental health problems, especially for young women. In a five-year follow-up, claim duration for disability benefits was long lasting for most claimants.

Purpose: To explore the preferable way of use and design of a work ability prognosis support tool for insurance physicians (IPs) and labour experts (LEs), based on a prediction model for future changes in work ability among individuals applying for a work disability benefit. Methods: We conducted three focus groups with professionals of the Dutch Social Security Institute (17 IPs and 7 LEs). Data were audio recorded and qualitatively analysed according to the main principles of thematic analysis. Results: Clarity and ease of use were mentioned as important features of the tool. Most professionals preferred to make their own judgement during the work disability assessment interview with the claimant and afterwards verify their evaluation with the tool. Concerning preferences on the design of the tool, dividing work disability claimants into categories based on the outcome of the prediction model was experienced as the most straightforward and clear way of presenting the results. Professionals expected that this encourages them to use the tool and act accordingly. Conclusions: The tool should be easy to access and interpret, to increase the chance that professionals will use it. This way it can optimally help professionals making accurate prognoses of future changes in work ability. ä IMPLICATIONS FOR REHABILITATIONA work ability prognosis support tool based on a prediction model for changes in work ability at one-year follow-up can help occupational health professionals in making accurate prognosis of individuals applying for a work disability benefit. To be used in occupational health practice, these tools should have a simple and easy-to-use design. Graphical risk presentation can be used to provide intuitive meaning to numerical information and support users' understanding. Taking professionals' preferences into account when developing these tools encourages professionals to use the tools and act accordingly.